/Bayesian-network-weighted-and-Gibbs-sampling-

Bayesian network using weighted and Gibbs sampling

Primary LanguagePythonMIT LicenseMIT

Bayesian-network-weighted-and-Gibbs-sampling-

Bayesian network implementation using weighted and Gibbs sampling

The network example used looks like that:

Network

The input format for that network is:

rede = BayesNet([('B', '', 0.9), ('M', '', 0.1), ('I', 'B M', {(T, T): 0.9, (T, F): 0.5, (F, T): 0.5, (F, F): 0.1}), ('G', 'B I M', {(T, T, T): 0.9, (T, T, F): 0.8, (T, F, T): 0.0, (T, F, F): 0.0, (F, T, T): 0.2, (F, T, F): 0.1, (F, F, T): 0.0, (F, F, F): 0.0}), ('J', 'G', {T: 0.9, F: 0.0}),])

You can adapt to any desired input.